




'''simple docstring'''


import json
import os
import re
import unittest

from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class  __lowercase    (	__magic_name__							,				unittest.TestCase			):
   _a    						=   CodeGenTokenizer
   _a    						=   CodeGenTokenizerFast
   _a    						=   True
   _a    						=   {"""add_prefix_space""": True}
   _a    						=   False







   def 		UpperCamelCase__      (						self   )					->     Tuple:
     super().setUp()

     # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
     __a								=       [
         'l',
         'o',
         'w',
         'e',
         'r',
         's',
         't',
         'i',
         'd',
         'n',
         '\u0120',
         '\u0120l',
         '\u0120n',
         '\u0120lo',
         '\u0120low',
         'er',
         '\u0120lowest',
         '\u0120newer',
         '\u0120wider',
         '<unk>',
         '<|endoftext|>',
     ]
     __a								=       dict(zip(UpperCamelCase   ,				range(len(UpperCamelCase   )   )   )   )
     __a								=       ['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
     __a								=       {'unk_token': '<unk>'}

     __a								=       os.path.join(self.tmpdirname   ,				VOCAB_FILES_NAMES['vocab_file']   )
     __a								=       os.path.join(self.tmpdirname   ,				VOCAB_FILES_NAMES['merges_file']   )
     with open(self.vocab_file   ,				'w'   ,				encoding='utf-8'   ) as fp:
       fp.write(json.dumps(UpperCamelCase   ) + '\n'   )
     with open(self.merges_file   ,				'w'   ,				encoding='utf-8'   ) as fp:
       fp.write('\n'.join(UpperCamelCase   )   )







   def 		UpperCamelCase__      (						self   ,				**UpperCamelCase   )					->     List[str]:
     kwargs.update(self.special_tokens_map   )
     return CodeGenTokenizer.from_pretrained(self.tmpdirname   ,				**UpperCamelCase   )







   def 		UpperCamelCase__      (						self   ,				**UpperCamelCase   )					->     List[str]:
     kwargs.update(self.special_tokens_map   )
     return CodeGenTokenizerFast.from_pretrained(self.tmpdirname   ,				**UpperCamelCase   )







   def 		UpperCamelCase__      (						self   ,				UpperCamelCase   )					->     Union[str, Any]:
     __a								=       'lower newer'
     __a								=       'lower newer'
     return input_text, output_text







   def 		UpperCamelCase__      (						self   )					->     Optional[int]:
     __a								=       CodeGenTokenizer(self.vocab_file   ,				self.merges_file   ,				**self.special_tokens_map   )
     __a								=       'lower newer'
     __a								=       ['\u0120low', 'er', '\u0120', 'n', 'e', 'w', 'er']
     __a								=       tokenizer.tokenize(UpperCamelCase   ,				add_prefix_space=UpperCamelCase   )
     self.assertListEqual(UpperCamelCase   ,				UpperCamelCase   )

     __a								=       tokens + [tokenizer.unk_token]
     __a								=       [14, 15, 10, 9, 3, 2, 15, 19]
     self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase   )   ,				UpperCamelCase   )







   def 		UpperCamelCase__      (						self   )					->     List[Any]:
     if not self.test_rust_tokenizer:
       return

     __a								=       self.get_tokenizer()
     __a								=       self.get_rust_tokenizer(add_prefix_space=UpperCamelCase   )

     __a								=       'lower newer'

     # Testing tokenization
     __a								=       tokenizer.tokenize(UpperCamelCase   ,				add_prefix_space=UpperCamelCase   )
     __a								=       rust_tokenizer.tokenize(UpperCamelCase   )
     self.assertListEqual(UpperCamelCase   ,				UpperCamelCase   )

     # Testing conversion to ids without special tokens
     __a								=       tokenizer.encode(UpperCamelCase   ,				add_special_tokens=UpperCamelCase   ,				add_prefix_space=UpperCamelCase   )
     __a								=       rust_tokenizer.encode(UpperCamelCase   ,				add_special_tokens=UpperCamelCase   )
     self.assertListEqual(UpperCamelCase   ,				UpperCamelCase   )

     # Testing conversion to ids with special tokens
     __a								=       self.get_rust_tokenizer(add_prefix_space=UpperCamelCase   )
     __a								=       tokenizer.encode(UpperCamelCase   ,				add_prefix_space=UpperCamelCase   )
     __a								=       rust_tokenizer.encode(UpperCamelCase   )
     self.assertListEqual(UpperCamelCase   ,				UpperCamelCase   )

     # Testing the unknown token
     __a								=       tokens + [rust_tokenizer.unk_token]
     __a								=       [14, 15, 10, 9, 3, 2, 15, 19]
     self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(UpperCamelCase   )   ,				UpperCamelCase   )







   def 		UpperCamelCase__      (						self   ,				*UpperCamelCase   ,				**UpperCamelCase   )					->     Any:
     # It's very difficult to mix/test pretokenization with byte-level
     # And get both CodeGen and Roberta to work at the same time (mostly an issue of adding a space before the string)
     pass







   def 		UpperCamelCase__      (						self   ,				UpperCamelCase=15   )					->     Any:
     for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"   ):
         __a								=       self.rust_tokenizer_class.from_pretrained(UpperCamelCase   ,				**UpperCamelCase   )

         # Simple input
         __a								=       'This is a simple input'
         __a								=       ['This is a simple input 1', 'This is a simple input 2']
         __a								=       ('This is a simple input', 'This is a pair')
         __a								=       [
             ('This is a simple input 1', 'This is a simple input 2'),
             ('This is a simple pair 1', 'This is a simple pair 2'),
         ]

         # Simple input tests
         self.assertRaises(UpperCamelCase   ,				tokenizer_r.encode   ,				UpperCamelCase   ,				max_length=UpperCamelCase   ,				padding='max_length'   )

         # Simple input
         self.assertRaises(UpperCamelCase   ,				tokenizer_r.encode_plus   ,				UpperCamelCase   ,				max_length=UpperCamelCase   ,				padding='max_length'   )

         # Simple input
         self.assertRaises(
             UpperCamelCase   ,				tokenizer_r.batch_encode_plus   ,				UpperCamelCase   ,				max_length=UpperCamelCase   ,				padding='max_length'   ,				)

         # Pair input
         self.assertRaises(UpperCamelCase   ,				tokenizer_r.encode   ,				UpperCamelCase   ,				max_length=UpperCamelCase   ,				padding='max_length'   )

         # Pair input
         self.assertRaises(UpperCamelCase   ,				tokenizer_r.encode_plus   ,				UpperCamelCase   ,				max_length=UpperCamelCase   ,				padding='max_length'   )

         # Pair input
         self.assertRaises(
             UpperCamelCase   ,				tokenizer_r.batch_encode_plus   ,				UpperCamelCase   ,				max_length=UpperCamelCase   ,				padding='max_length'   ,				)







   def 		UpperCamelCase__      (						self   )					->     List[Any]:
     __a								=       CodeGenTokenizer.from_pretrained(self.tmpdirname   ,				pad_token='<pad>'   )

     # Simple input
     __a								=       'This is a simple input'
     __a								=       ['This is a simple input looooooooong', 'This is a simple input']
     __a								=       ('This is a simple input', 'This is a pair')
     __a								=       [
         ('This is a simple input loooooong', 'This is a simple input'),
         ('This is a simple pair loooooong', 'This is a simple pair'),
     ]

     __a								=       tokenizer.pad_token_id

     __a								=       tokenizer(UpperCamelCase   ,				padding='max_length'   ,				max_length=30   ,				return_tensors='np'   )
     __a								=       tokenizer(UpperCamelCase   ,				padding=UpperCamelCase   ,				truncate=UpperCamelCase   ,				return_tensors='np'   )
     __a								=       tokenizer(*UpperCamelCase   ,				padding='max_length'   ,				max_length=60   ,				return_tensors='np'   )
     __a								=       tokenizer(UpperCamelCase   ,				padding=UpperCamelCase   ,				truncate=UpperCamelCase   ,				return_tensors='np'   )

     # s
     # test single string max_length padding
     self.assertEqual(out_s['input_ids'].shape[-1]   ,				30   )
     self.assertTrue(pad_token_id in out_s['input_ids']   )
     self.assertTrue(0 in out_s['attention_mask']   )

     # s2
     # test automatic padding
     self.assertEqual(out_sa['input_ids'].shape[-1]   ,				33   )
     # long slice doesn't have padding
     self.assertFalse(pad_token_id in out_sa['input_ids'][0]   )
     self.assertFalse(0 in out_sa['attention_mask'][0]   )
     # short slice does have padding
     self.assertTrue(pad_token_id in out_sa['input_ids'][1]   )
     self.assertTrue(0 in out_sa['attention_mask'][1]   )

     # p
     # test single pair max_length padding
     self.assertEqual(out_p['input_ids'].shape[-1]   ,				60   )
     self.assertTrue(pad_token_id in out_p['input_ids']   )
     self.assertTrue(0 in out_p['attention_mask']   )

     # p2
     # test automatic padding pair
     self.assertEqual(out_pa['input_ids'].shape[-1]   ,				52   )
     # long slice pair doesn't have padding
     self.assertFalse(pad_token_id in out_pa['input_ids'][0]   )
     self.assertFalse(0 in out_pa['attention_mask'][0]   )
     # short slice pair does have padding
     self.assertTrue(pad_token_id in out_pa['input_ids'][1]   )
     self.assertTrue(0 in out_pa['attention_mask'][1]   )







   def 		UpperCamelCase__      (						self   )					->     int:
     __a								=       '$$$'
     __a								=       CodeGenTokenizer.from_pretrained(self.tmpdirname   ,				bos_token=UpperCamelCase   ,				add_bos_token=UpperCamelCase   )

     __a								=       'This is a simple input'
     __a								=       ['This is a simple input 1', 'This is a simple input 2']

     __a								=       tokenizer.bos_token_id

     __a								=       tokenizer(UpperCamelCase   )
     __a								=       tokenizer(UpperCamelCase   )

     self.assertEqual(out_s.input_ids[0]   ,				UpperCamelCase   )
     self.assertTrue(all(o[0] == bos_token_id for o in out_sa.input_ids   )   )

     __a								=       tokenizer.decode(out_s.input_ids   )
     __a								=       tokenizer.batch_decode(out_sa.input_ids   )

     self.assertEqual(decode_s.split()[0]   ,				UpperCamelCase   )
     self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa   )   )







   @slow
   def 		UpperCamelCase__      (						self   )					->     Tuple:
     __a								=       CodeGenTokenizer.from_pretrained('Salesforce/codegen-350M-mono'   )

     __a								=       '\nif len_a > len_b:\n    result = a\nelse:\n    result = b\n\n\n\n#'
     __a								=       '\nif len_a > len_b:      result = a\nelse:      result = b'

     __a								=       tokenizer.encode(UpperCamelCase   )
     __a								=       ['^#', re.escape('<|endoftext|>'   ), '^\'\'\'', '^"""', '\n\n\n']
     __a								=       tokenizer.decode(UpperCamelCase   ,				truncate_before_pattern=UpperCamelCase   )
     self.assertEqual(UpperCamelCase   ,				UpperCamelCase   )







   def 		UpperCamelCase__      (						self   )					->     Tuple:
     pass









'''simple docstring'''


from multiprocessing import Lock, Pipe, Process

# lock used to ensure that two processes do not access a pipe at the same time
UpperCAmelCase_					=   Lock()


def     SCREAMING_SNAKE_CASE							(   a_						:				str					,       a_						:				Tuple					,       a_						:				Dict					,       a_						:				Optional[Any]					,       a_						:				str					,       a_						:				Any					,       a_						:				Optional[Any]      ):
  global process_lock

  # we perform n swaps since after n swaps we know we are sorted
  # we *could* stop early if we are sorted already, but it takes as long to
  # find out we are sorted as it does to sort the list with this algorithm
  for i in range(0					,       10      ):
    if (i + position) % 2 == 0 and r_send is not None:
      # send your value to your right neighbor
      process_lock.acquire()
      r_send[1].send(a_      )
      process_lock.release()

      # receive your right neighbor's value
      process_lock.acquire()
      __a								=       rr_cv[0].recv()
      process_lock.release()

      # take the lower value since you are on the left
      __a								=       min(a_					,       a_      )
    elif (i + position) % 2 != 0 and l_send is not None:
      # send your value to your left neighbor
      process_lock.acquire()
      l_send[1].send(a_      )
      process_lock.release()

      # receive your left neighbor's value
      process_lock.acquire()
      __a								=       lr_cv[0].recv()
      process_lock.release()

      # take the higher value since you are on the right
      __a								=       max(a_					,       a_      )
    # after all swaps are performed, send the values back to main
  result_pipe[1].send(a_      )


def     SCREAMING_SNAKE_CASE							(   a_						:				List[str]      ):
  __a								=       []
  __a								=       []
  # initialize the list of pipes where the values will be retrieved
  for _ in arr:
    result_pipe.append(Pipe()      )
  # creates the processes
  # the first and last process only have one neighbor so they are made outside
  # of the loop
  __a								=       Pipe()
  __a								=       Pipe()
  process_array_.append(
      Process(
          target=a_					,       args=(0, arr[0], None, temp_rs, None, temp_rr, result_pipe[0])					,       )      )
  __a								=       temp_rs
  __a								=       temp_rr

  for i in range(1					,       len(a_      ) - 1      ):
    __a								=       Pipe()
    __a								=       Pipe()
    process_array_.append(
        Process(
            target=a_					,       args=(i, arr[i], temp_ls, temp_rs, temp_lr, temp_rr, result_pipe[i])					,       )      )
    __a								=       temp_rs
    __a								=       temp_rr

  process_array_.append(
      Process(
          target=a_					,       args=(
              len(a_      ) - 1,
              arr[len(a_      ) - 1],
              temp_ls,
              None,
              temp_lr,
              None,
              result_pipe[len(a_      ) - 1],
          )					,       )      )

  # start the processes
  for p in process_array_:
    p.start()

  # wait for the processes to end and write their values to the list
  for p in range(0					,       len(a_      )      ):
    __a								=       result_pipe[p][0].recv()
    process_array_[p].join()
  return arr


def     SCREAMING_SNAKE_CASE							(   ):
  __a								=       list(range(10					,       0					,       -1      )      )
  print('Initial List'      )
  print(*a_      )
  __a								=       odd_even_transposition(a_      )
  print('Sorted List\n'      )
  print(*a_      )


if __name__ == "__main__":
  main()



